Explore the CAMELS project in this 27-minute conference talk by Paco Villaescusa Navarro from the Flatiron Institute. Dive into the application of astrostatistics and machine learning tools to galaxy formation and evolution. Discover how the CAMELS project utilizes data science techniques to analyze vast amounts of astronomical data, including spectra from Integral Field Unit surveys and galaxy morphology from imaging data. Learn about the project's role in outlier detection, linking observations with theoretical models, and its potential impact on our understanding of galaxy formation physics. Gain insights into how the CAMELS project contributes to maximizing the benefits of data-driven tools in the field of galaxy formation and evolution.
Overview
Syllabus
The CAMELS project â–¸ Paco Villaescusa Navarro (Flatiron)
Taught by
Kavli Institute for Theoretical Physics
Related Courses
-
Dust Properties of Galaxies from a Data-Driven Hierarchical Model - John Forbes
-
Finding Simple Structures in Complex Datasets - Dalya Baron
-
Outliers - How I Learned to Love Them, and Why You Should Too
-
Learning to Simulate the Universe with Deep Learning - Elena Giusarma
-
Optimizing Target Selection for Low-Redshift Galaxy Surveys - Elise Darragh Ford
-
Galaxy Zoo in the Deep Learning Era - Mike Walmsley
